Noise Based Deepfake Detection via Multi-Head Relative-Interaction

• DOI: 10.1609/aaai.v37i12.26701
• Publication Date: 2023-06-27T18:27:36Z
• Authors: Tianyi Wang; Kam Pui Chow
• Keywords: Robustness

Deepfake brings huge and potential negative impacts to our daily lives. As the real-life videos circulated on Internet become more authentic, most existing detection algorithms have failed since few visual differences can be observed between an authentic video a one. However, forensic traces are always retained within synthesized videos. In this study, we present noise-based model, NoiseDF for short, which focuses underlying noise left behind particular, enhance RIDNet denoiser extract features from cropped face background squares of image frames. Meanwhile, devise novel Multi-Head Relative-Interaction method evaluate degree interaction faces backgrounds that plays pivotal role in task. Besides outperforming state-of-the-art models, visualization extracted has further displayed evidence proved robustness approach.